Compiler Optimization Testing Based on Optimization-Guided Equivalence Transformations

• URL: http://arxiv.org/abs/2504.04321v1
• Date: Sun, 06 Apr 2025 01:37:57 GMT
• Title: Compiler Optimization Testing Based on Optimization-Guided Equivalence Transformations
• Authors: Jingwen Wu, Jiajing Zheng, Zhenyu Yang, Zhongxing Yu,
• Abstract summary: We propose a metamorphic testing approach inspired by compiler optimizations.<n>Our approach first employs tailored code construction strategies to generate input programs that satisfy optimization conditions.<n>By comparing the outputs of pre- and post-transformation programs, this approach effectively identifies incorrect optimization bugs.
• Score: 3.2987550056134873
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Compiler optimization techniques are inherently complex, and rigorous testing of compiler optimization implementation is critical. Recent years have witnessed the emergence of testing approaches for uncovering incorrect optimization bugs, but these approaches rely heavily on the differential testing mechanism, which requires comparing outputs across multiple compilers. This dependency gives rise to important limitations, including that (1) the tested functionality must be consistently implemented across all compilers and (2) shared bugs remain undetected. Thus, false alarms can be produced and significant manual efforts will be required. To overcome the limitations, we propose a metamorphic testing approach inspired by compiler optimizations. The approach is driven by how to maximize compiler optimization opportunities while effectively judging optimization correctness. Specifically, our approach first employs tailored code construction strategies to generate input programs that satisfy optimization conditions, and then applies various compiler optimization transformations to create semantically equivalent test programs. By comparing the outputs of pre- and post-transformation programs, this approach effectively identifies incorrect optimization bugs. We conducted a preliminary evaluation of this approach on GCC and LLVM, and we have successfully detected five incorrect optimization bugs at the time of writing. This result demonstrates the effectiveness and potential of our approach.

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